Dissertation > Excellent graduate degree dissertation topics show

Research on Edge Detection Algorithm Based on Wavelet Transformation

Author: WangLan
Tutor: WuJin
School: Wuhan University of Science and Technology
Course: Control Theory and Control Engineering
Keywords: Edge detection Wavelet transformation B-spline wavelet Modulus local maxima Block adaptive
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 568
Quote: 8
Read: Download Dissertation

Abstract


Edge is the most basic feature of images, which includes the most part information of images. So obtaining the edge image has turned into a hot spot in research on image processing and analysis technology, So far, many algorithms have been presented in edge detection field. But the problems in anti-noise and edge location were not well resolved because of the complexity and inherent problems of edge detection. The reason is that the noise and edge were both high-frequency signals and it was hardly solved to distinguish between noises and edges from local high-frequency signals using current algorithms.“Time-frequency”multi-scale analysis of wavelet transform brings new ways to image edge detection.Wavelet analysis is a new tool of time-frequency analysis after Fourier analysis. It can effectively analyze signal singularity point and detect edges while restraining noise because of its good time-frequency local property and multi-scale characteristics. So, as a powerful tool of researching non-stationary signal, it is paid more attention in the field of information processing and is widely applied in image processing technology.In this paper, the prospect for the development and application of wavelet transformation is introduced firstly and then the research status of image edge detection is given. After studying the characteristics of the classical edge detection algorithm, summing up the advantages and disadvantages of each, wavelet theory applied in edge detection is introduced. According to the evaluation criteria of edge detection, in the considering of the best edge filter design, we identified the criteria for the selection of wavelet bases and choose the fourth-order B-spline wavelet as the wavelet bases through experimental comparison. In the use of wavelet modulus local maxima, for the selection of local modulus maxima, we calculate it along the direction of gradient of the modulus maxima; for threshold selection, we use method of blocking adaptive threshold. Contrast to conventional modulus maxima methods, experiments show that the algorithm in this paper achieved better results at the same time having good noise suppression.

Related Dissertations

  1. Research on Recognition of Fabric Weave Pattern Based on Space-Frequency Domain,TS101.923
  2. Research on Noise Reducation and Color Interpolation Algorithms Based on Bayer Pattern Images for Digital Camera,TP391.41
  3. Research and Implementaion of Image Processing Algorithm Based on FPGA,TP391.41
  4. Research of Visibility Improving Method for Underwater Observation Video Images,TP391.41
  5. Pattern recognition method based weather radar monitoring and analysis of digital products,TN959.4
  6. The Research on the Vehicle-borne GPR Detection Technology of the Railway Subgrade Defects,U216.3
  7. Detection Algorithms on the Surface Edge Defects of Galvanized Sheet Based on Digital Image,TP274
  8. Research on Detecting Optical Fiber Geometric Parameter Based on Machine Vision,TN253
  9. Tire Defects Inspection Based on Digital Image Processing,TP274
  10. Researches on Technique of Extracting the Edge Information from Remote Sensing Image Based on Mathematical Morphology,TP751
  11. The Study for Two-dimensional Geometric Size Measurement Algorithm of Parts Based on Image Processing,TP391.41
  12. Reservoir Prediction Research of QWS Block in the Southeast of Sichuan,P618.13
  13. Edge Detection of Leukemia Cell Image Based on Spiking Neural Network,TP391.41
  14. Mathematical morphology combined with remote sensing image invariant moments Target Detection Method,TP751
  15. Ant colony algorithm for image edge detection,TP391.41
  16. Morphological Image Edge Detection by Using Multi-structuring Elements and Multi-scale Structure Elements,TP391.41
  17. Study of Condenser Copper Tube Location Based on Visual Localization,TP391.41
  18. Research on the Technologies of Special Content-Based Erotic Image Filtering,TP391.41
  19. Strip surface defect detection key technology research,TP274.4
  20. Online Visual Detect System and Key Technology of Glass Bottles,TP274.4
  21. Image Edge Detection Technique,TP391.41

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile